Reddit mentions of Quantitative Trading: How to Build Your Own Algorithmic Trading Business

This is better than buying and praying but be wary of many factors when designing a trading system.

​

1. Overfitting: When you are backtesting any strategy, there is a danger of overfitting the dataset. A more appropriate way to model this is to separate your data into training and test sets. Then you design your system using the training dataset, then test the performance against the test set. I like to randomly sample the historical data or randomly generate data that has a similar shape to make sure that I'm not overfitting.
   
2. Tax: If you haven't included the tax drag on your investment strategy, you could see the real returns be negative. For example, if I hold a token for over 12 months in the US, my tax rate is half (around 20%) of what I would pay for a short-term gain (nearly 40%). If you are trading in a taxable account, this can be ruinous. If you're trading in a Roth or other tax-free (deferred) account, go nuts!
   
3. Market slippage: You'll frequently find that you cannot enter the market exactly at the market close. Luckily in cryptos you don't have to worry about overnight gaps, but just because the historical data shows a closing price is no guarantee that you can fill your orders at that price. What is the gap between your bid-ask spread? What is the depth of the order book at each day's close?
   
4. Psychology: Unless you are a sociopath, you won't follow your strategy perfectly. You'll sell too early or buy too late, even if your technical indicators are correct.
   
5. Transaction Costs: Every transaction in the crypto space carries a significant cost with it. It can be .25% or more. With a 10-day moving average, you will be trading frequently and those fees will accumulate.
   
6. Risk Management: How large of a position will you allocate to ETH? What do you do when you have a market that tanks overnight, bypassing your stop-losses? How much are you willing to risk on a specific signal?
   
   Be careful. What you have discovered is valuable, but if it were that easy, everyone would be doing it. It doesn't mean it can't be done, but identifying a buy/sell signals is only 5% of your trading system.
   
   ​
   
   If you are interested in developing these types of systems as a career, consider reading Quantitative Trading: How to Build Your Own Algorithmic Trading Business by Ernest P. Chan. It's an excellent starting point for building trading systems.
   
   ​
   
   https://www.amazon.com/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889
   
   ​
   
   I have made all of these mistakes and more over the past 10 years as a professional investor. I love this stuff, so I'm happy to answer any questions you guys have about your systems. Maybe I can help save you a little pain and suffering!

> Can you recommend any books on coding quant strategies?

http://www.quantstart.com/articles/quantitative-finance-reading-list

Favorites I've read so far:

• Inside the Black Box (if you're totally new to the concept)
  
  
• Quantitative Trading (the second book, Algorithmic trading goes deeper into implementing strategies, also good)
  
  
• Trading Systems (a GREAT book on implementation and the process of testing a strategy)
  
  
• Active Portfolio Management (Kind of a classic, more theory than implementation, requires some fundamental understanding of MPT, CAPM and related concepts. Good chapter on multi-factor risk models)
  
  Also
  
  
• Algorithmic Trading and DMA (Still on my bookshelf, haven't gotten around to reading it yet, but it's supposed to be the book on market microstructure, so if you'er interested in HFT or level-2 algos, this is a good starting point)
  
  Edit: Be prepared to spend about 3 months just randomly browsing Investopedia to crack through all the jargon :)
  
  Also, these guys have some pretty rockin' videos on on everything finance, from "WTF is an ETF?" to "WTF is a European Call Option?" to "How do I manage my pension?", especially useful if you're in the UK. The videos helped me a lot when I was getting started at my current job.
  
  https://www.youtube.com/user/MoneyWeekVideos/videos

Omar, the first thing you need is a little bit of Python. Personally I'm a fan of Code Academy.

If you're looking to understand a little more about common types of trading algorithms, check out this blog post. We've been drafting it a while, and you inspired us to publish it!

I'm also a huge fan of Ernie Chan's book which really explains a lot about the "business" of algorithmic trading.

They're not really "backtesting resources" but Ernie Chan's books all use matlab code examples, and he has all of the full example code on his website (viewable with a password obtained from the book)

• Quantitative Trading: How to Build Your Own Algorithmic Trading Business
  
  
• Algorithmic Trading: Winning Strategies and Their Rationale
  
  
• Machine Trading: Deploying Computer Algorithms to Conquer the Markets
  

• Quantative Trading by Edward Chan
  
  
• Beat The Forex Dealer by Agustin Silvani
  
  
• The Creature from Jekyll Island by G. Edward Griffin
  
  
• Freakonomics by Steve Levitt
  
  
• Hot Commodities by Jim Rogers
  
  

That's fine, then. My main concern was that you might be putting your money on the line!

I am not sure that an automated momentum system can't work. In fact, many CTAs (commodity trading advisors... a kind of hedge fund) made consistent returns in 2000-2009 by following pretty simple momentum strategies - generally moving averages or moving average crossovers on a 100-300 day window. Note that the timescale is much longer than yours, and also note that most of those CTAs have been in drawdown since about 2010 (ie they've lost money or just about broken even for the last four years).

But I am pretty certain that an intraday trading system based on trashy, discredited technical analysis isn't going to yield consistent profits, especially when applied by someone who is trading for the first time.

One way to tell if a trader knows what they are doing is to listen to their language - if they talk about technical indicators, fibonacci retracement, elliott waves, entry and exit points, MACD etc then they are a quack. If they talk about regression, signal processing, traing and test sets, regularization, bias/variance etc then there's a chance that they know what they're talking about.

There is fifty years of history building mathematical tools for analysing random processes, making time series forecasts, building regression models, and analysing models out of sample, all of which is generally ignored by the quacks who rely on spurious "indicators" and "entry/exit points". A good place to start is this book -

http://www-bcf.usc.edu/~gareth/ISL/

and this is a good book for when you've progressed beyond the intermediate level

http://statweb.stanford.edu/~tibs/ElemStatLearn/

There are two books by Ernest Chan about quantitative trading that frankly don't tell you anything that will be immediately applicable to creating a strategy (there's no secret sauce) but they do give you a good high level overview of what building a quantitative trading system is all about

http://www.amazon.co.uk/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889/ref=sr_1_2?ie=UTF8&qid=1406963471&sr=8-2&keywords=ernest+chan
http://www.amazon.co.uk/Algorithmic-Trading-Winning-Strategies-Rationale/dp/1118460146/ref=sr_1_1?ie=UTF8&qid=1406963471&sr=8-1&keywords=ernest+chan

Hope that's helpful.

And that there is a lot of spoofing, half filled orders and similar by bots going on on the real market. Then you have the more physical real world things that the broke you use might be down, there was a circuit breaker for the price that was executed and your algo gets triggered the wrong way

I could recommend this book that talks about algo trading from a general viewpoint https://www.amazon.com/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889